https://github.com/zsailer/skspline

A Scikit-learn interface on Scipy's spline.
https://github.com/zsailer/skspline

scikit-learn scipy

Last synced: 2 months ago
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A Scikit-learn interface on Scipy's spline.

• Host: GitHub
• URL: https://github.com/zsailer/skspline
• Owner: Zsailer
• Created: 2018-04-11T04:41:02.000Z (about 8 years ago)
• Default Branch: master
• Last Pushed: 2019-07-02T23:26:30.000Z (almost 7 years ago)
• Last Synced: 2025-04-08T17:53:28.445Z (about 1 year ago)
• Topics: scikit-learn, scipy
• Language: Python
• Size: 108 KB
• Stars: 0
• Watchers: 0
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.rst

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README

          
Scikit Spline

=============

A Scikit-learn interface on Scipy's ``Univariate Spline``.

.. code-block:: python

  import matplotlib.pyplot as plt

  import numpy as np

  import skspline

  # Simulate data.

  x = np.linspace(0, 4, 100)

  y = 10*np.sin(x)

  yerr = np.random.randn(len(y))

  # Add noise to y.

  y = y + yerr

  # Initialize a Scikit Spline model and fit.

  m = skspline.Spline(k=2)

  m.fit(x, y)

  # Get model

  xmodel = np.linspace(0, 4, 1000)

  ymodel = m.predict(xmodel)

  # plot data and model

  plt.scatter(x, y)

  plt.plot(xmodel,ymodel, color='k', linewidth=5)

  plt.show()

.. image:: docs/_img/example.png

  :scale: 50 %